Edge detection in hyperspectral imaging: multivariate statistical approaches

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Edge detection in hyperspectral imaging: multivariate statistical approaches

Conference Paper (2006)

Author(s)

S Verzakov (TU Delft - Electrical Engineering, Mathematics and Computer Science)

P Paclik (TU Delft - Electrical Engineering, Mathematics and Computer Science)

RPW Duin (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Research Group

Multimedia Computing

CWTS 0.75 <= JFIS < 2.00 Conference contrib. refereed

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https://resolver.tudelft.nl/uuid:18e6dace-bca9-4171-b66d-62aa3ab6ad50

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Publication Year

2006

Research Group

Multimedia Computing

Pages (from-to)

551-559

Publisher

Springer

ISBN (print)

3-540-37236-9

Event

Joint IAPR International Workshops SSPR 2006 and SPR 2006, Hong Kong, China (2006-08-17 - 2006-08-19), Heidelberg

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Abstract

Edgedetectioniswelldevelopedareaofimageanalysis.Manyvariouskindsoftechniquesweredesignedforone-channelimages.Also,aconsiderableattentionwaspaidtoedgedetectionincolor,multispectral,andhyperspectralimages.However,therearestillmanyopenissuesinedgedetectioninmultichannelimages.Forexample,eventhede¿nitionofmultichanneledgeisratherempiricalandisnotwellestablished.Inthispaperstatisticalpatternrecognitionmethodologyisusedtoapproachtheproblemofedgedetectionbyconsideringimagepixelsaspointsinamultidimensionalfeaturespace.Appropriatemultivariatetechniquesareusedtoretrieveinformationwhichcanbeusefulforedgedetection.Theproposedapproachesweretestedonthereal-worlddata.

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